LLM and RAG Engineering Fundamentals with Python

Discover how to engineer intelligent applications by combining the power of Large Language Models (LLMs) with Retrieval Augmented Generation (RAG). This course provides a foundational understanding of LLM and RAG engineering, enabling you to design and implement practical generative AI solutions. What you'll learn: * Understand the foundational architecture and capabilities of Large Language Models. * Apply Python programming to interact with and utilize LLM APIs. * Grasp the principles and benefits of Retrieval Augmented Generation (RAG). * Design and implement basic RAG pipelines for contextual responses. * Explore fundamental prompt engineering techniques for effective LLM interaction. * Learn basic concepts of deploying LLM-powered applications. * Consider ethical implications and best practices in generative AI development. Starting with core AI and LLM concepts, the course progresses to practical RAG system design and implementation, concluding with deployment considerations and ethical guidelines. This course is designed for absolute beginners with no prior experience in AI or machine learning, seeking to enter the field of generative AI engineering. Begin your journey into building intelligent generative AI applications today.